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Title: Self-tuning fuzzy controller for air-conditioning systems
Keywords: Temperature, Relative Humidity, Air-Conditioning System, Fuzzy Logic, Neural Networks, Fuzzy Neural Networks
Issue Date: 29-Jan-2004
Citation: ZHENG XIAOQING (2004-01-29). Self-tuning fuzzy controller for air-conditioning systems. ScholarBank@NUS Repository.
Abstract: This project studies the control of a chilled water air-conditioning system using a fuzzy logic controller and a fuzzy neural network controller. The simultaneous control of space temperature and relative humidity can be achieved by varying the supply airflow rate and chilled water flow rate respectively. In this work, fuzzy logic is successfully applied to the controller design so that the difficulty of getting the accurate model of the system is avoided. The fuzzy controller is insensitive to the coupling of the temperature and relative humidity. It also shows favorable set point tracking and disturbance rejection abilities. To resolve the tedious tuning procedure for the fuzzy controller, a neural network is incorporated to form a fuzzy neural network controller. The fuzzy neural network controller combines the advantages of fuzzy logic and neural networks. The fuzzy controller realizes self-tuning through training of the neural network using measured plant input-output data. The designed fuzzy neural network controller performs well when applied to the air-conditioning system under test.
Appears in Collections:Master's Theses (Open)

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